Abstract
This paper concentrates upon similarity between objects described by vectors of nominal features. It proposes non-metric measures for evaluating the similarity between: (a) two identical values in a feature, (b) two different values in a feature, (c) two objects. The paper suggests that similarity is dependent upon the context: It is influenced by the given set of objects, and the concept under discussion. The proposed Context-Similarity measure was tested, and the paper presents comparisons with other measures. The comparisons suggest that compared to other measures, the Context-Similarity suites best for natural concepts.
Cite
CITATION STYLE
Biberman, Y. (1994). A context similarity measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 784 LNCS, pp. 49–63). Springer Verlag. https://doi.org/10.1007/3-540-57868-4_50
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